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Neuro-controller implementation for the embedded control system for mini-greenhouse.

Vasyl Teslyuk1, Ivan Tsmots1, Natalia Kryvinska2

  • 1Department of Automated Control Systems, Lviv Polytechnic National University, Lviv, Ukraine.

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|December 11, 2023
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Summary
This summary is machine-generated.

This study introduces a modular neuro-controller for embedded systems, leveraging artificial neural networks for efficient control. The hardware, based on STM32 microcontrollers, offers a cost-effective solution for intelligent control applications.

Keywords:
Artificial neural networkControl systemIntelligentmini-greenhouseNeuro-controllerSTM32

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Area of Science:

  • Control Systems Engineering
  • Artificial Intelligence
  • Embedded Systems

Background:

  • Traditional control systems face limitations in embedded applications.
  • Neural networks offer advanced control capabilities but pose implementation challenges.
  • Existing solutions often lack modularity and cost-effectiveness.

Purpose of the Study:

  • To propose a novel neuro-controller for embedded systems.
  • To design a modular neuro-controller structure for rapid development.
  • To demonstrate a cost-effective implementation using STM32 microcontrollers.

Main Methods:

  • Development of a modular neuro-controller architecture.
  • Design of a functioning algorithm and data processing model using artificial neural networks.
  • Hardware implementation utilizing STM32 microcontroller, sensors, and actuators.

Main Results:

  • A functional neuro-controller enabling processing of technological data.
  • A modular design facilitating system improvement during development.
  • A low-cost hardware implementation suitable for embedded applications.

Conclusions:

  • The proposed neuro-controller effectively integrates artificial neural networks into embedded control systems.
  • The modular design and software-based neural network implementation allow for rapid adaptation and improvement.
  • The STM32-based system provides a practical and economical solution for intelligent control, exemplified by a mini-greenhouse application.